A tunnel section low-carbon lighting intelligent control method and system with multiple dimming modes

Abstract

The application discloses a kind of low-carbon lighting intelligent control methods of multiple light adjustment modes of tunnel section, comprising the following steps: based on the traffic flow distribution prediction model of tunnel section through vehicle data information is constructed;Based on the weather brightness distribution model of tunnel outside road section weather brightness data information is constructed;Based on tunnel section parameter, traffic flow distribution prediction model and weather brightness distribution model, tunnel section lighting light adjustment scheme is constructed;Based on time series, tunnel section through vehicle data information and tunnel outside road section weather brightness data information are acquired and predicted processing is carried out, and real-time light adjustment strategy of tunnel section is determined based on the prediction processing result;Realized by constructing traffic flow distribution prediction model and weather brightness distribution model, vehicle data information and tunnel outside road section weather brightness data information are predicted and processed, and light adjustment mode of tunnel section is selected to control the luminance of tunnel each road section, so as to greatly improve energy-saving effect under the condition of ensuring driving safety.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to a method and system for intelligently controlling low-carbon lighting with multiple dimming modes in a tunnel section. Background Art

[0002] The current tunnel dimming mode can achieve time-based dimming, and operation and maintenance personnel can set the dimming according to inspection experience. Although it has a certain level of intelligence, it still has certain shortcomings in dimming precision and energy saving. The current tunnel lighting control system has a single dimming mode and the decision-making algorithm is not intelligent enough, resulting in insufficient adaptability of the system to changes in tunnel structure and traffic flow, resulting in the inability to achieve effective energy saving effects. Summary of the Invention

[0003] In order to overcome the shortcomings of the existing technology, the present invention provides a low-carbon lighting intelligent control method and system with multiple dimming modes in tunnel sections. By constructing a traffic flow distribution prediction model and a weather brightness distribution model, the vehicle data information and the weather brightness data information of the section outside the tunnel are predicted and processed, and the tunnel section dimming mode is selected to control the brightness of the lamps in each section of the tunnel, thereby greatly improving the energy saving effect while ensuring driving safety.

[0004] In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical solutions:

[0005] In a first aspect, the present application provides a method for intelligently controlling low-carbon lighting in a tunnel section with multiple dimming modes, comprising the following steps:

[0006] S101, constructing a traffic flow distribution prediction model based on the data information of vehicles passing through the tunnel section;

[0007] S102, constructing a weather brightness distribution model based on weather brightness data information of the road section outside the tunnel;

[0008] S103: Constructing a tunnel section lighting dimming solution based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model;

[0009] S104: Obtain data information of vehicles passing through the tunnel section and weather brightness data information of the section outside the tunnel based on the time series and perform prediction processing, and determine a real-time dimming strategy for the tunnel section based on the prediction processing results.

[0010] Furthermore, constructing a traffic flow distribution prediction model based on the vehicle data information of the tunnel section includes the following steps:

[0011] Fitting distribution processing is performed on the vehicle data information passing through the tunnel section based on Weibull distribution;

[0012] Based on the unit time length, the traffic flow of the tunnel section processed by fitting distribution is calculated through the vehicle data information to obtain the traffic flow per unit time;

[0013] Divide the traffic flow per unit time into traffic flow types;

[0014] Statistics are collected on the time taken by each traffic flow type and the proportion of passing vehicles.

[0015] Furthermore, the traffic flow type includes a low traffic flow type, a medium traffic flow type, and a high traffic flow type.

[0016] Furthermore, the process of classifying the traffic flow per unit time into traffic flow types includes the following steps:

[0017] Setting a first vehicle flow threshold and a second vehicle flow threshold, wherein the second vehicle flow threshold is greater than the first vehicle flow threshold;

[0018] defining a traffic volume that is less than or equal to a first traffic volume threshold as a low traffic volume type;

[0019] The traffic flow that is greater than the first traffic flow threshold and less than the second traffic flow threshold is defined as the medium traffic flow type;

[0020] A traffic volume greater than or equal to the second traffic volume threshold is defined as a high traffic volume type.

[0021] Furthermore, constructing a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel includes the following steps:

[0022] Count the proportion of sunny weather types and non-sunny weather types in spring, summer, autumn and winter respectively;

[0023] A quadratic function was used to fit the daily daytime brightness changes in spring, summer, autumn and winter, and the seasonal brightness fitting curves were obtained.

[0024] Furthermore, based on tunnel section parameters, traffic flow distribution prediction model and weather brightness distribution model, constructing a tunnel section lighting dimming solution includes the following steps:

[0025] Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section;

[0026] Obtain the brightness characteristics of light outside the tunnel, perform brightness prediction based on the weather brightness distribution model, generate section lighting control signals based on the brightness prediction results and the light environment requirements of each tunnel section, and transmit them to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section, and build a stepless dimming mode tunnel section lighting dimming solution;

[0027] When a vehicle is detected approaching, traffic flow prediction processing is performed based on the traffic flow distribution prediction model. Based on the traffic flow prediction results, a road section lighting control signal is generated and transmitted to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section and build a tunnel section lighting dimming solution with vehicle-based dimming mode.

[0028] Furthermore, based on the time series, the vehicle data information of the tunnel section and the weather brightness data information of the section outside the tunnel are obtained and predicted, and the real-time dimming strategy of the tunnel section is determined based on the prediction processing results, including the following steps:

[0029] Based on the traffic flow distribution prediction model, the traffic flow data information of the vehicles passing through the tunnel section is predicted and processed to obtain the traffic flow prediction value per unit time; based on the weather brightness distribution model, the brightness data information of the section outside the tunnel is predicted and processed to obtain the brightness prediction value per unit time;

[0030] If an accident is detected in the tunnel or maintenance work is planned, the fixed power dimming mode is selected;

[0031] If the brightness is lower than the nighttime brightness setting threshold, the enhanced circuit is closed according to the time interval between late night and nighttime, and the basic circuit adopts the vehicle-mounted lighting and fixed power dimming mode;

[0032] If the predicted traffic flow value per unit time is greater than the traffic flow setting threshold, and the brightness is greater than the night brightness setting threshold, the vehicle-based dimming mode is selected;

[0033] If the predicted traffic flow per unit time is less than the traffic flow setting threshold, and the brightness is greater than the night brightness setting threshold, the stepless dimming mode is selected.

[0034] A second aspect of the present application provides a tunnel section multi-dimming mode low-carbon lighting intelligent control system, comprising:

[0035] A first model building unit is used to build a traffic flow distribution prediction model based on the vehicle data information passing through the tunnel section;

[0036] The second model building unit is used to build a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel;

[0037] A dimming pattern scheme generation unit is used to construct a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model;

[0038] A first data collection unit is used to collect data information of vehicles passing through the tunnel section based on a time series and transmit the data to the processor unit;

[0039] The second data acquisition unit is used to collect weather brightness data information of the road section outside the tunnel based on time series and transmit it to the processor unit;

[0040] The processor unit predicts and processes the data of vehicles passing through the tunnel section and the weather brightness data of the section outside the tunnel based on the traffic flow distribution prediction model and the weather brightness distribution model, and generates a dimming mode control signal and transmits it to the lighting controller to control the brightness of each section of the tunnel;

[0041] The lamp controller is used to receive the dimming mode control signal transmitted by the processor unit and control the working status of the lamps in each section of the tunnel based on the dimming mode control signal.

[0042] Furthermore, the first model building unit builds a traffic flow distribution prediction model based on the vehicle data information of the tunnel section, including:

[0043] Fitting distribution processing is performed on the vehicle data information passing through the tunnel section based on Weibull distribution;

[0044] Based on the unit time length, the traffic flow of the tunnel section processed by fitting distribution is calculated through the vehicle data information to obtain the traffic flow per unit time;

[0045] Divide the traffic flow per unit time into traffic flow types;

[0046] Statistics are collected on the time taken by each traffic flow type and the proportion of passing vehicles.

[0047] Furthermore, the second model building unit builds a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel, including:

[0048] Count the proportion of sunny weather types and non-sunny weather types in spring, summer, autumn and winter respectively;

[0049] A quadratic function was used to fit the daily daytime brightness changes in spring, summer, autumn and winter, and the seasonal brightness fitting curves were obtained.

[0050] Furthermore, the dimming mode scheme generating unit constructs a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model, including:

[0051] Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section;

[0052] The luminance prediction processing is performed based on the weather luminance distribution model, the luminance prediction processing result and the light environment requirement of each road section of the tunnel are used to determine the road section lamp control signal to control the luminance of the tunnel road section, and a constant dimming mode tunnel road section lighting dimming scheme is constructed.

[0053] The traffic flow prediction processing is performed based on the traffic flow distribution prediction model, the traffic flow prediction result is used to determine the road section lamp control signal to control the luminance of the tunnel road section, and a vehicle-dependent dimming mode tunnel road section lighting dimming scheme is constructed.

[0054] Further, the processor unit performs prediction processing on the vehicle data information of the tunnel road section and the weather luminance data information of the road section outside the tunnel based on the traffic flow distribution prediction model and the weather luminance distribution model, and generates a dimming mode control signal, which includes:

[0055] The traffic flow prediction processing is performed on the vehicle data information of the tunnel road section based on the traffic flow distribution prediction model, and the luminance prediction processing is performed on the weather luminance data information of the road section outside the tunnel based on the weather luminance distribution model, to obtain the traffic flow prediction value per unit time and the luminance prediction value per unit time.

[0056] If an accident in the tunnel is detected or a maintenance work plan is arranged, a fixed power dimming mode control signal is generated;

[0057] If the luminance is less than the night luminance setting threshold, a strengthened loop light-off control signal and a basic loop fixed power control signal are generated;

[0058] If the traffic flow prediction value per unit time is less than the traffic flow setting threshold and the luminance is greater than the night luminance setting threshold, a vehicle-dependent dimming mode control signal is generated;

[0059] If the traffic flow prediction value per unit time is greater than the traffic flow setting threshold and the luminance is greater than the night luminance setting threshold, a constant dimming mode control signal is generated.

[0060] Further, the lamp controller controls the working state of the lamps of each road section of the tunnel based on the dimming mode control signal, which includes:

[0061] If the dimming mode control signal transmitted by the processor unit and received by the lamp controller is a fixed power dimming mode control signal, the lamp controller controls the lamps of each road section of the tunnel to be in a fixed power dimming mode working state;

[0062] If the dimming mode control signal transmitted by the processor unit and received by the lamp controller is a vehicle-dependent dimming mode control signal, the lamp controller controls the lamps of each road section of the tunnel to be in a vehicle-dependent dimming mode working state;

[0063] If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a stepless dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in the stepless dimming mode working state.

[0064] The beneficial effects of this application are: by constructing a traffic flow distribution prediction model and a weather brightness distribution model, the vehicle data information and the weather brightness data information of the road section outside the tunnel are predicted and processed, and the tunnel section dimming mode is selected to control the brightness of the lamps in each section of the tunnel, thereby achieving greatly improved energy saving while ensuring driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0066] Figure 1 This is a schematic diagram of the steps of a low-carbon lighting intelligent control method with multiple dimming modes in a tunnel section of the present invention. DETAILED DESCRIPTION

[0067] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0068] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0069] Example 1:

[0070] A method for intelligently controlling low-carbon lighting with multiple dimming modes in a tunnel section includes the following steps:

[0071] S101, constructing a traffic flow distribution prediction model based on the data information of vehicles passing through the tunnel section;

[0072] Based on a time series, data on vehicles passing through a tunnel section is obtained, and a Weibull distribution is applied to the data. The data is then used to calculate the traffic volume of vehicles passing through the tunnel section according to different unit time lengths. The unit time length can be days or hours, and is not specifically limited in the present invention. For example, if the unit time length is hourly, the traffic volume of vehicles passing through the tunnel section, which has been subjected to the fitted distribution, is calculated based on the hourly unit time, thereby obtaining hourly traffic volume data.

[0073] Building a traffic flow distribution prediction model based on the vehicle data information passing through the tunnel section includes the following steps:

[0074] Fitting distribution processing is performed on the vehicle data information passing through the tunnel section based on Weibull distribution;

[0075] Based on the unit time length, the traffic flow of the tunnel section processed by fitting distribution is calculated through the vehicle data information to obtain the traffic flow per unit time;

[0076] Divide the traffic flow per unit time into traffic flow types;

[0077] Statistics are collected on the time taken by each traffic flow type and the proportion of passing vehicles.

[0078] The traffic volume per unit time is divided into traffic volume types, including low traffic volume type, medium traffic volume type, and high traffic volume type. A first traffic volume threshold and a second traffic volume threshold are set, and the second traffic volume threshold is greater than the first traffic volume threshold. Traffic volume less than or equal to the first traffic volume threshold is defined as low traffic volume type, traffic volume greater than the first traffic volume threshold and less than the second traffic volume threshold is defined as medium traffic volume type, and traffic volume greater than or equal to the second traffic volume threshold is defined as high traffic volume type. Traffic volume types can be divided according to actual usage. Simply increasing or decreasing the number of traffic volume types is within the scope of protection of the present invention.

[0079] Count the time spent by each traffic flow type and the percentage of vehicles passing through. Count the time spent by low traffic flow type, the time spent by medium traffic flow type, and the time spent by high traffic flow type separately. For example, count the number of hours spent by each traffic flow type using 24 hours per day as the time unit. Count the number of vehicles passing through low traffic flow type, medium traffic flow type, and high traffic flow type separately, and calculate the percentage of vehicles passing through each traffic flow type.

[0080] S102, constructing a weather brightness distribution model based on weather brightness data information of the road section outside the tunnel;

[0081] The weather brightness data information of the tunnel outer road section is obtained based on a time sequence. The weather brightness data information of the tunnel outer road section can be divided into spring, summer, autumn and winter weather brightness data information of the tunnel outer road section according to the brightness change of each day. According to the brightness change of each day, a quadratic function can be used for fitting to obtain the distribution of the weather brightness characteristics of the tunnel outer road section over time. The weather types include sunny, overcast, rainy and cloudy.

[0082] The weather brightness distribution model is constructed based on the weather brightness data information of the tunnel outer road section, including the following steps:

[0083] The proportions of sunny weather types and non-sunny weather types in spring, summer, autumn and winter are respectively counted.

[0084] The brightness change of each day in spring, summer, autumn and winter is respectively fitted by using a quadratic function to obtain the quarterly brightness fitting curve.

[0085] S103, based on the tunnel road section parameter, the traffic flow distribution prediction model and the weather brightness distribution model, a tunnel road section lighting dimming scheme is constructed;

[0086] Based on the tunnel road section parameter, the traffic flow distribution prediction model and the weather brightness distribution model, a tunnel road section lighting dimming scheme is constructed. The construction of the tunnel road section lighting dimming scheme includes a fixed power dimming mode, a stepless dimming mode and a car-following dimming mode. The tunnel road section parameters are obtained. The tunnel road section includes a tunnel entrance road section, a tunnel transition road section, a tunnel basic road section, a tunnel exit road section and a tunnel emergency parking area road section. The lengths of each road section of the tunnel road section are counted respectively. The light environment requirements of each road section are calculated according to the lengths of each road section of the tunnel road section. The lighting lamps are selected to complete the lamp deployment of the tunnel road section to ensure the safety of tunnel driving, and the fixed power dimming mode tunnel road section lighting dimming scheme is constructed. The light brightness characteristics outside the tunnel are obtained. The brightness prediction processing is carried out based on the weather brightness distribution model. According to the brightness prediction processing result and the light environment requirement of each road section of the tunnel, the road section lamp control signal is generated and transmitted to the corresponding lamp controller of the tunnel road section to control the brightness of the tunnel road section and ensure the safety of tunnel driving, and the stepless dimming mode tunnel road section lighting dimming scheme is constructed. When a car is detected, the traffic flow prediction processing is carried out based on the traffic flow distribution prediction model. The road section lamp control signal is generated based on the traffic flow prediction result and transmitted to the corresponding lamp controller of the tunnel road section to control the brightness of the tunnel road section and ensure the safety of tunnel driving, and the car-following dimming mode tunnel road section lighting dimming scheme is constructed.

[0087] Based on the tunnel road section parameter, the traffic flow distribution prediction model and the weather brightness distribution model, the tunnel road section lighting dimming scheme is constructed, including the following steps:

[0088] Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section;

[0089] Obtain the brightness characteristics of light outside the tunnel, perform brightness prediction based on the weather brightness distribution model, generate section lighting control signals based on the brightness prediction results and the light environment requirements of each tunnel section, and transmit them to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section and build a stepless dimming mode tunnel section lighting dimming solution;

[0090] When a vehicle is detected approaching, traffic flow prediction processing is performed based on the traffic flow distribution prediction model. Based on the traffic flow prediction results, a road section lighting control signal is generated and transmitted to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section and build a tunnel section lighting dimming solution with vehicle-based dimming mode.

[0091] S104, obtaining data information of vehicles passing through the tunnel section and weather brightness data information of the section outside the tunnel based on the time series and performing prediction processing, and determining a real-time dimming strategy for the tunnel section based on the prediction processing results;

[0092] Based on the time series, the data information of vehicles passing through the tunnel section and the weather brightness data information of the section outside the tunnel are obtained to perform traffic flow prediction and brightness prediction processing to obtain the traffic flow prediction value per unit time and the brightness prediction value per unit time. The tunnel section dimming mode is selected based on the prediction processing results. The tunnel section lighting dimming solutions include fixed power dimming mode, stepless dimming mode and vehicle-mounted dimming mode.

[0093] Acquiring tunnel section vehicle passing data information and tunnel section weather brightness data information based on time series and performing prediction processing, and determining the tunnel section real-time dimming strategy based on the prediction processing results includes the following steps:

[0094] Based on the traffic flow distribution prediction model, the traffic flow data information of the vehicles passing through the tunnel section is predicted and processed to obtain the traffic flow prediction value per unit time; based on the weather brightness distribution model, the brightness data information of the section outside the tunnel is predicted and processed to obtain the brightness prediction value per unit time;

[0095] If an accident is detected in the tunnel or maintenance work is planned, the fixed power dimming mode is selected;

[0096] If the brightness is lower than the nighttime brightness setting threshold, the enhanced circuit is closed according to the time interval between late night and nighttime, and the basic circuit adopts the vehicle-mounted lighting and fixed power dimming mode;

[0097] If the predicted traffic flow value per unit time is greater than the traffic flow setting threshold, and the brightness is greater than the night brightness setting threshold, the vehicle-based dimming mode is selected;

[0098] If the predicted traffic volume per unit time is less than the traffic volume threshold, and the brightness is greater than the night brightness threshold, the stepless dimming mode is selected.

[0099] The above is a kind of low-carbon lighting intelligent control method of multiple dimming modes of tunnel section provided in the embodiment of the application, and the following is a kind of low-carbon lighting intelligent control system of multiple dimming modes of tunnel section provided in the embodiment of the application.

[0100] A kind of low-carbon lighting intelligent control system of multiple dimming modes of tunnel section, comprising:

[0101] The first model construction unit is used to construct a traffic volume distribution prediction model based on the tunnel section passing vehicle data information;

[0102] The second model construction unit is used to construct a weather brightness distribution model based on the tunnel outside section weather brightness data information;

[0103] The dimming mode scheme generation unit is used to construct a tunnel section lighting dimming scheme based on the tunnel section parameters, traffic volume distribution prediction model and weather brightness distribution model;

[0104] The first data acquisition unit is used to acquire tunnel section passing vehicle data information based on time series, and transmit to the processor unit;

[0105] The second data acquisition unit is used to acquire tunnel outside section weather brightness data information based on time series, and transmit to the processor unit;

[0106] The processor unit is used to predict and process tunnel section passing vehicle data information and tunnel outside section weather brightness data information based on traffic volume distribution prediction model and weather brightness distribution model, and generate dimming mode control signal to transmit to the lamp controller to control the brightness of each section of the tunnel;

[0107] The lamp controller is used to receive dimming mode control signal transmitted by the processor unit, and control the working state of the lamp of each section of the tunnel based on the dimming mode control signal.

[0108] The first model construction unit is used to construct a traffic volume distribution prediction model based on the tunnel section passing vehicle data information, and the first model construction unit constructs a traffic volume distribution prediction model based on the tunnel section passing vehicle data information, including the following steps:

[0109] The tunnel section passing vehicle data information is fitted and distributed based on Weibull distribution;

[0110] The tunnel section passing vehicle data information after fitting and distribution processing is calculated and processed based on the length of unit time to obtain the traffic volume per unit time.

[0111] Divide the traffic flow per unit time into traffic flow types;

[0112] Statistics are collected on the time taken by each traffic flow type and the proportion of passing vehicles.

[0113] The second model building unit is used to build a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel. The second model building unit builds a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel, including the following steps:

[0114] Count the proportion of sunny weather types and non-sunny weather types in spring, summer, autumn and winter respectively;

[0115] A quadratic function was used to fit the daily daytime brightness changes in spring, summer, autumn and winter, and the seasonal brightness fitting curves were obtained.

[0116] The dimming mode scheme generation unit is used to construct a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model. The tunnel section lighting dimming scheme includes a fixed power dimming mode scheme, a stepless dimming mode scheme, and a vehicle-based dimming mode scheme. The dimming mode scheme generation unit constructs a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model, including the following steps:

[0117] Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section;

[0118] Perform brightness prediction based on the weather brightness distribution model. Determine the section lighting control signal based on the brightness prediction results and the light environment requirements of each tunnel section to control the brightness of the tunnel section. Build a stepless dimming mode tunnel section lighting dimming solution.

[0119] Traffic flow prediction processing is performed based on the traffic flow distribution prediction model. The road section lighting control signal is determined based on the traffic flow prediction results to control the brightness of the tunnel section, and a tunnel section lighting dimming solution with vehicle-based dimming mode is constructed.

[0120] The processor unit predicts and processes the vehicle data information passing through the tunnel section and the weather brightness data information of the section outside the tunnel based on the traffic flow distribution prediction model and the weather brightness distribution model, and generates a dimming mode control signal to transmit to the lamp controller to control the brightness of each section of the tunnel. The prediction processing includes traffic flow prediction processing and brightness prediction processing to obtain the traffic flow prediction value per unit time and the brightness prediction value per unit time. The dimming mode control signal includes a fixed power dimming mode control signal, a stepless dimming mode control signal and a vehicle-mounted dimming mode control signal.

[0121] The processor unit predicts and processes the vehicle data information passing through the tunnel section and the weather brightness data information of the section outside the tunnel based on the vehicle flow distribution prediction model and the weather brightness distribution model, and generates a dimming mode control signal, including the following steps:

[0122] Based on the traffic flow distribution prediction model, the traffic flow data information of the vehicles passing through the tunnel section is predicted and processed to obtain the traffic flow prediction value per unit time; based on the weather brightness distribution model, the brightness data information of the section outside the tunnel is predicted and processed to obtain the brightness prediction value per unit time;

[0123] If an accident is detected in the tunnel, or a maintenance operation is scheduled, a fixed power dimming mode control signal is generated;

[0124] If the brightness is less than the nighttime brightness setting threshold, a light-off control signal for the enhanced circuit and a fixed power control signal for the basic circuit are generated;

[0125] If the predicted traffic flow value per unit time is less than the traffic flow setting threshold and the brightness is greater than the night brightness setting threshold, a vehicle-based dimming mode control signal is generated;

[0126] If the predicted traffic flow per unit time is greater than the traffic flow setting threshold and the brightness is greater than the night brightness setting threshold, a stepless dimming mode control signal is generated.

[0127] The lamp controller is used to receive the dimming mode control signal transmitted by the processor unit and control the working state of the lamps in each section of the tunnel based on the dimming mode control signal. The dimming mode control signal includes a fixed power dimming mode control signal, a vehicle-mounted dimming mode control signal, and a stepless dimming mode control signal. The lamp controller controls the working state of the lamps in each section of the tunnel based on the dimming mode control signal, including:

[0128] If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a fixed power dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in a fixed power dimming mode working state;

[0129] If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a vehicle-based dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in the vehicle-based dimming mode working state;

[0130] If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a stepless dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in the stepless dimming mode working state.

[0131] Table 1 shows the energy consumption and energy saving rate of the tunnel section under the stepless dimming mode, as shown below

[0132]

[0133] Table 2 shows the energy consumption and energy saving rate of the tunnel section in stepless dimming mode, as shown below

[0134]

[0135] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0136] The terms "first", "second" and "third" etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can, for example, be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0137] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0139] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0140] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A low-carbon lighting intelligent control method with multiple dimming modes in tunnel sections, characterized by: The following steps are involved: S101: Constructing a traffic flow distribution prediction model based on vehicle data information on a tunnel section, including the following steps: Fitting distribution processing is performed on the vehicle data information passing through the tunnel section based on Weibull distribution; Based on the unit time length, the traffic flow of the tunnel section processed by fitting distribution is calculated through the vehicle data information to obtain the traffic flow per unit time; Divide the traffic flow per unit time into traffic flow types; Count the time occupied by each traffic flow type and the proportion of passing vehicles; S102: Constructing a weather brightness distribution model based on weather brightness data information of the road section outside the tunnel, including the following steps: Count the proportion of sunny weather types and non-sunny weather types in spring, summer, autumn and winter respectively; A quadratic function was used to fit the daily daytime brightness changes in spring, summer, autumn, and winter, and the seasonal brightness fitting curves were obtained. S103: Constructing a tunnel section lighting dimming solution based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model, including the following steps: Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section; Obtain the brightness characteristics of light outside the tunnel, perform brightness prediction based on the weather brightness distribution model, generate section lighting control signals based on the brightness prediction results and the light environment requirements of each tunnel section, and transmit them to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section and build a stepless dimming mode tunnel section lighting dimming solution; When a vehicle is detected, traffic flow prediction is performed based on the traffic flow distribution prediction model. Based on the traffic flow prediction results, a road section lighting control signal is generated and transmitted to the lighting controller of the corresponding tunnel section to control the brightness of the tunnel section and establish a tunnel section lighting dimming solution with vehicle-based dimming mode; S104, acquiring data information of vehicles passing through the tunnel section and weather brightness data information of the section outside the tunnel based on the time series and performing prediction processing, and determining a real-time dimming strategy for the tunnel section based on the prediction processing results, including the following steps: Based on the traffic flow distribution prediction model, the traffic flow data information of the vehicles passing through the tunnel section is predicted and processed to obtain the traffic flow prediction value per unit time; based on the weather brightness distribution model, the brightness data information of the section outside the tunnel is predicted and processed to obtain the brightness prediction value per unit time; If an accident is detected in the tunnel or maintenance work is planned, the fixed power dimming mode is selected; If the brightness is lower than the nighttime brightness setting threshold, the enhanced circuit is closed according to the time interval between late night and nighttime, and the basic circuit adopts the vehicle-mounted lighting and fixed power dimming mode; If the predicted traffic flow value per unit time is greater than the traffic flow setting threshold, and the brightness is greater than the night brightness setting threshold, the vehicle-based dimming mode is selected; If the predicted traffic flow per unit time is less than the traffic flow setting threshold, and the brightness is greater than the night brightness setting threshold, the stepless dimming mode is selected.

2. The intelligent control method for low-carbon lighting with multiple dimming modes in tunnel sections according to claim 1 is characterized in that: The process of classifying the traffic flow per unit time into traffic flow types includes the following steps: Setting a first vehicle flow threshold and a second vehicle flow threshold, wherein the second vehicle flow threshold is greater than the first vehicle flow threshold; defining a traffic volume that is less than or equal to a first traffic volume threshold as a low traffic volume type; The traffic flow that is greater than the first traffic flow threshold and less than the second traffic flow threshold is defined as the medium traffic flow type; A traffic volume greater than or equal to the second traffic volume threshold is defined as a high traffic volume type.

3. A tunnel section multi-dimming mode low-carbon lighting intelligent control system, used to implement the tunnel section multi-dimming mode low-carbon lighting intelligent control method according to any one of claims 1-2, characterized in that: include: A first model building unit is used to build a traffic flow distribution prediction model based on the vehicle data information passing through the tunnel section; The second model building unit is used to build a weather brightness distribution model based on the weather brightness data information of the road section outside the tunnel; A dimming mode scheme generation unit is used to construct a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model; A first data collection unit is used to collect data information of vehicles passing through the tunnel section based on a time series and transmit the data to the processor unit; The second data acquisition unit is used to collect weather brightness data information of the road section outside the tunnel based on a time series and transmit it to the processor unit; The processor unit predicts and processes the data of vehicles passing through the tunnel section and the weather brightness data of the section outside the tunnel based on the traffic flow distribution prediction model and the weather brightness distribution model, and generates a dimming mode control signal and transmits it to the lighting controller to control the brightness of each section of the tunnel; The lamp controller is used to receive the dimming mode control signal transmitted by the processor unit and control the working status of the lamps in each section of the tunnel based on the dimming mode control signal.

4. The tunnel section multi-dimming mode low-carbon lighting intelligent control system according to claim 3 is characterized in that: The dimming mode scheme generating unit constructs a tunnel section lighting dimming scheme based on tunnel section parameters, a traffic flow distribution prediction model, and a weather brightness distribution model, including: Calculate the light environment requirements of each tunnel section based on the tunnel section parameters, and build a fixed power dimming mode tunnel section lighting dimming solution based on the calculation results of the light environment requirements of each tunnel section; Perform brightness prediction based on the weather brightness distribution model. Determine the section lighting control signal based on the brightness prediction results and the light environment requirements of each tunnel section to control the brightness of the tunnel section and build a stepless dimming mode tunnel section lighting dimming solution. Traffic flow prediction processing is performed based on the traffic flow distribution prediction model. The control signal of the road section lamps is determined based on the traffic flow prediction results to control the brightness of the tunnel section, and a tunnel section lighting dimming solution with vehicle-based dimming mode is constructed.

5. The tunnel section multi-dimming mode low-carbon lighting intelligent control system according to claim 3 is characterized in that: The processor unit predicts and processes the vehicle data information passing through the tunnel section and the weather brightness data information of the section outside the tunnel based on the vehicle flow distribution prediction model and the weather brightness distribution model, and generates a dimming mode control signal including: Based on the traffic flow distribution prediction model, the traffic flow data information of the vehicles passing through the tunnel section is predicted and processed to obtain the traffic flow prediction value per unit time; based on the weather brightness distribution model, the brightness data information of the section outside the tunnel is predicted and processed to obtain the brightness prediction value per unit time; If an accident is detected in the tunnel or a maintenance operation is scheduled, a fixed power dimming mode control signal is generated; If the brightness is lower than the nighttime brightness setting threshold, a light-off control signal for the enhanced circuit and a fixed power control signal for the basic circuit are generated; If the predicted traffic flow value per unit time is less than the traffic flow setting threshold and the brightness is greater than the night brightness setting threshold, a vehicle-based dimming mode control signal is generated; If the predicted traffic flow per unit time is greater than the traffic flow setting threshold and the brightness is greater than the night brightness setting threshold, a stepless dimming mode control signal is generated.

6. The tunnel section multi-dimming mode low-carbon lighting intelligent control system according to claim 3 is characterized in that: The lamp controller controls the working state of lamps in each section of the tunnel based on the dimming mode control signal, including: If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a fixed power dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in a fixed power dimming mode working state; If the dimming mode control signal transmitted by the processor unit received by the lamp controller is a vehicle-based dimming mode control signal, the lamp controller is controlled to control the lamps of each section of the tunnel to be in the vehicle-based dimming mode working state; If the dimming mode control signal received by the lamp controller from the processor unit is a stepless dimming mode control signal, the lamp controller controls the lamps in each section of the tunnel to be in the stepless dimming mode working state.

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